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Y. Shi^1,2, Q. Mao^1,3,4, H. Xu¹, W. Hu³, Y. Mu⁴ and G. Wang¹

¹School of Remote Sensing and Information Engineering, Wuhan University, China
²State Key Laboratory of Rail Transit Vehicle System, Southwest Jiaotong University, Chengdu, China
³, Wuhan Hanning Rail Transit Technology Corporation Limited, China
⁴, Hubei luojia laboratory, Wuhan, China

doi:10.4203/ccc.15.17.8

Y. Shi, Q. Mao, H. Xu, W. Hu, Y. Mu, G. Wang, "Continuous Mobile Measurement System for Rail Profile Based on Multi-Line Laser and Combined Navigation", in J. Pombo, (Editor), "Proceedings of the Seventh International Conference on Railway Technology: Research, Development and Maintenance ", Civil-Comp Press, Edinburgh, UK, Online volume: CCC 15, Paper 17.8, 2026, doi:10.4203/ccc.15.17.8

Keywords: rail profiles, continuous measurement, line laser, multi?sensor fusion, combined navigation, point cloud reconstruction.

Abstract

A continuous mobile measurement and 3D reconstruction method for rail profiles based on multi-line structured light and integrated navigation is proposed. A multi-sensor fusion localization model integrating IMU, DMI, and GNSS is developed to achieve high-precision pose estimation under dynamic conditions. A unified coordinate transformation framework is established for consistent point cloud representation. An improved ICP algorithm incorporating initial pose and structural constraints is proposed for accurate multi-temporal point cloud registration and continuous reconstruction. Experimental results demonstrate that the static measurement accuracy is better than 0.10 mm, with an optimal accuracy of 0.06 mm. Under dynamic conditions at 60 km/h, the measurement deviation is maintained within 0.10 mm. The proposed method enables the transformation from discrete cross-sectional measurement to continuous spatial reconstruction, significantly improving measurement accuracy and efficiency.

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Front Page Browse CCC CCP CSETS CTR IJRT Other Authors Search Purchase Guide FAQ Contact us	Civil-Comp Conferences ISSN 2753-3239 CCC: 15 PROCEEDINGS OF THE SEVENTH INTERNATIONAL CONFERENCE ON RAILWAY TECHNOLOGY: RESEARCH, DEVELOPMENT AND MAINTENANCE Edited by: J. Pombo Paper 17.8 Continuous Mobile Measurement System for Rail Profile Based on Multi-Line Laser and Combined Navigation Y. Shi^1,2, Q. Mao^1,3,4, H. Xu¹, W. Hu³, Y. Mu⁴ and G. Wang¹ ¹School of Remote Sensing and Information Engineering, Wuhan University, China ²State Key Laboratory of Rail Transit Vehicle System, Southwest Jiaotong University, Chengdu, China ³, Wuhan Hanning Rail Transit Technology Corporation Limited, China ⁴, Hubei luojia laboratory, Wuhan, China doi:10.4203/ccc.15.17.8 Full Bibliographic Reference for this paper Y. Shi, Q. Mao, H. Xu, W. Hu, Y. Mu, G. Wang, "Continuous Mobile Measurement System for Rail Profile Based on Multi-Line Laser and Combined Navigation", in J. Pombo, (Editor), "Proceedings of the Seventh International Conference on Railway Technology: Research, Development and Maintenance ", Civil-Comp Press, Edinburgh, UK, Online volume: CCC 15, Paper 17.8, 2026, doi:10.4203/ccc.15.17.8 Keywords: rail profiles, continuous measurement, line laser, multi?sensor fusion, combined navigation, point cloud reconstruction. Abstract A continuous mobile measurement and 3D reconstruction method for rail profiles based on multi-line structured light and integrated navigation is proposed. A multi-sensor fusion localization model integrating IMU, DMI, and GNSS is developed to achieve high-precision pose estimation under dynamic conditions. A unified coordinate transformation framework is established for consistent point cloud representation. An improved ICP algorithm incorporating initial pose and structural constraints is proposed for accurate multi-temporal point cloud registration and continuous reconstruction. Experimental results demonstrate that the static measurement accuracy is better than 0.10 mm, with an optimal accuracy of 0.06 mm. Under dynamic conditions at 60 km/h, the measurement deviation is maintained within 0.10 mm. The proposed method enables the transformation from discrete cross-sectional measurement to continuous spatial reconstruction, significantly improving measurement accuracy and efficiency. download the full-text of this paper (PDF, 15 pages, 957 Kb) go to the previous paper go to the next paper return to the table of contents return to the volume description
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